The Forecasting Performance of Seasonal and Nonlinear Models

The Forecasting Performance of Seasonal and Nonlinear Models

Journal

  • Journal title: Asian Economic and Financial Review
  • ISSN: 2305-2147 (print) 2222-6737 (online)
  • Publisher: Aess
  • Country of publisher: pakistan
  • Date added to EuroPub: 2017/May/11

Subject and more

  • LCC Subject Category: Finance and Financial Services, Economics
  • Publisher's keywords: Seasonality, Nonlinearity, Interval forecasts, Density forecasts, Forecast evaluation tests
  • Language of fulltext: english
  • Full-text formats available: PDF

AUTHORS

    Houda Ben Hadj Boubaker| The Higher Institute of Management of Tunisia, Tunisia

EDITORIAL INFORMATION

FULL TEXT

ABSTRACT

In this paper, we compare the forecasting performance of seasonal and nonlinear autoregressive models in terms of point, interval, and densityforecasts for the growth rates of the Tunisian industrial production, for theperiod 1976:1- 2006:2. Our results suggest that the point forecastsgenerated by the linear models perform better than those provided by thenonlinear models at all horizons. By contrast, the analysis of interval anddensity forecasts at horizons of one and three quarters provide an evidentsupport for the nonlinear models, this result is in line with the literature.Thus, our findings assess the usefulness of nonlinear models to investigatethe dynamic behavior of economic systems and to produce accurateforecasts.

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